Fabric defect detection method based on improved YOLOv8n
The invention discloses a fabric defect detection method based on improved YOLOv8n. The method comprises the following steps: firstly, acquiring a fabric defect image data set; secondly, preprocessing the defect image sample of the fabric based on the defect type and position, including defect label...
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Format: | Patent |
Sprache: | chi ; eng |
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Zusammenfassung: | The invention discloses a fabric defect detection method based on improved YOLOv8n. The method comprises the following steps: firstly, acquiring a fabric defect image data set; secondly, preprocessing the defect image sample of the fabric based on the defect type and position, including defect labeling and data enhancement, and dividing a data set; then, a YOLOv8n algorithm model is improved, and the improved YOLOv8n model is used for training the data set; and finally, inputting a to-be-detected fabric defect image into the trained improved YOLOv8n model for identification to obtain a detection result.
本发明公开了一种基于改进YOLOv8n的织物疵点检测方法。该方法首先采集织物疵点图像数据集;然后基于缺陷类型和位置对织物的缺陷图像样本进行预处理,包括缺陷标注和数据增强,并对数据集进行划分;接着对YOLOv8n算法模型进行改进,并用改进后的YOLOv8n模型对数据集进行训练;最后将待检测的织物疵点图像输入至训练后的改进YOLOv8n模型进行识别,获得检测结果。 |
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